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The estimation of animal abundance : and related parameters
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ISBN: 0470233915 9780470233917 Year: 1994 Publisher: London: Edward Arnold,

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Efficiency analysis by production frontiers : the nonparametric approach
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ISBN: 0792300289 9401076944 9400926456 9780792300281 Year: 1989 Volume: 12 Publisher: Dordrecht : Kluwer,

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Optimal design: an introduction to the theory for parameter estimation
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ISBN: 0412229102 9400959141 9400959125 9780412229107 Year: 1980 Publisher: London Chapman and Hall

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Estimation in conditionally heteroscedastic time series models
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ISBN: 3540211357 9783540211358 Year: 2005 Publisher: Berlin: Springer,

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Semiparametric theory and missing data
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ISBN: 9780387324487 0387324488 1441921850 9786610743841 1280743840 0387373454 Year: 2006 Publisher: New York, N.Y. Springer

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Missing data arise in almost all scientific disciplines. In many cases, the treatment of missing data in an analysis is carried out in a casual and ad-hoc manner, leading, in many cases, to invalid inference and erroneous conclusions. In the past 20 years or so, there has been a serious attempt to understand the underlying issues and difficulties that come about from missing data and their impact on subsequent analysis. There has been a great deal written on the theory developed for analyzing missing data for finite-dimensional parametric models. This includes an extensive literature on likelihood-based methods and multiple imputation. More recently, there has been increasing interest in semiparametric models which, roughly speaking, are models that include both a parametric and nonparametric component. Such models are popular because estimators in such models are more robust than in traditional parametric models. The theory of missing data applied to semiparametric models is scattered throughout the literature with no thorough comprehensive treatment of the subject. This book combines much of what is known in regard to the theory of estimation for semiparametric models with missing data in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is at a level that is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.


Book
Identifiability of parametric models
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ISBN: 0080349293 1322556210 1483155951 9780080349299 Year: 1987 Publisher: Oxford Pergamon


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Discrete techniques of parameter estimation : the equation error formulation
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ISBN: 0824714555 9780824714550 Year: 1973 Publisher: New York : Marcel Dekker,

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On multiple test procedures for finding deviating parameters
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ISBN: 9122015949 9789122015949 Year: 1993 Volume: 22 22 Publisher: Stockholm Almqvist and Wiksell


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Introduction to bioinformatics
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ISBN: 9780198794141 0198794142 Year: 2019 Publisher: Oxford, United Kingdom : Oxford University Press,

Nonlinear statistical modeling : proceedings of the thirteenth International Symposium in Economic Theory and Econometrics : essays in honor of Takeshi Amemiya
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ISBN: 052166246X 9780521169264 9781139175203 9780521662468 0521169267 1139175203 Year: 2001 Publisher: Cambridge : Cambridge University Press,

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Abstract

This collection brings together important contributions by leading econometricians on (i) parametric approaches to qualitative and sample selection models, (ii) nonparametric and semi-parametric approaches to qualitative and sample selection models, and (iii) nonlinear estimation of cross-sectional and time series models. The advances achieved here can have important bearing on the choice of methods and analytical techniques in applied research.

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